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Alphabet Plans $75B In Capex This Year Amid AI Data Center Push

Feb 05, 2025 - bisnow.com
Google's parent company, Alphabet, plans to invest $75 billion in capital expenditures in 2025 to enhance its artificial intelligence (AI) capabilities, focusing primarily on technical infrastructure such as servers, data centers, and networking. This investment is $17 billion more than Wall Street's projections and follows a $58 billion capex spend in 2024. Alphabet's move aligns with other U.S. tech giants like Meta and Microsoft, which are also increasing their investments in AI infrastructure. Meta plans to spend between $60 billion and $65 billion, while Microsoft aims for $80 billion in capex for AI-ready data centers in 2025.

Alphabet CEO Sundar Pichai addressed concerns about the competitive landscape, particularly regarding Chinese startup DeepSeek's new AI model, which claims to be more cost-efficient. Pichai noted a shift in computing resources from training AI models to inference computing for customer-facing applications, which he views positively. He emphasized that the decreasing cost of AI usage will enable more feasible use cases, driving significant opportunities. Alphabet also expanded its cloud infrastructure by establishing 11 new cloud regions and data center campuses in 2024, with a fourth-quarter capex of $14 billion primarily allocated to technical infrastructure.

Key takeaways:

  • Alphabet plans to invest $75B in capital expenditures in 2025, focusing on AI business growth, primarily in technical infrastructure such as servers, data centers, and networking.
  • Alphabet's planned investment is $17B more than Wall Street's projection, with financial analysts estimating a $58B capex spend for the current year.
  • Meta and Microsoft are also increasing their capital expenditures in AI infrastructure, with Meta planning $60B-$65B and Microsoft $80B for 2025.
  • Alphabet's CEO Sundar Pichai emphasized the shift towards "inference" computing for AI applications and expressed optimism about the cost-effectiveness and potential of AI use cases.
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